Preoperative clinical radiomics model based on deep learning in prognostic assessment of patients with gallbladder carcinoma.

ABSTRACT:

Objective

We aimed to develop a preoperative clinical radiomics survival prediction model based on the radiomics features via deep learning to provide a reference basis for preoperative assessment and treatment decisions for patients with gallbladder carcinoma (GBC).

Methods

A total of 168 GBC patients who underwent preoperative upper abdominal enhanced CT from one high-volume medical center between January 2011 to December 2020 were retrospectively analyzed. The region of interest (ROI) was manually outlined by two physicians using 3D Slicer software to establish a nnU-Net model. The DeepSurv survival prediction model was developed by combining radiomics features and preoperative clinical variables.

Results

A total of 1502 radiomics features were extracted from the R

SUBMITTER: Jin Z 

PROVIDER: S-EPMC11863838 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature